Description Usage Arguments Details Value Author(s) Examples

View source: R/GroupClustering.R

posthoc is used to group or cluster the effects of liner, generalised linear and generalised linear mixed models according to significance of pairwise tests comparing the levels of the effects.

1 2 3 4 5 6 7 | ```
posthoc (Model, EffectIndices = NULL, EffectLabels = NULL,
EffectsMatrix = NULL, ParBootstrap = FALSE, Nboots = 999,
SignificanceLevel = 0.05, UpperCase = FALSE,
RankLabels = TRUE, WaldApproximation = FALSE,
CalcClusters = FALSE, QUIET = TRUE, PlotAdj = FALSE,
digits = 4, padjust = NULL, Scale = 1.0, Location = 0.0,
isBinomialModel = FALSE, BackTransform = TRUE)
``` |

`Model` |
a model of class lm, glm, glmerMod, lme or gls. |

`EffectIndices` |
a vector containing the indices of the effects to be analysed (default = NULL, indicating that all the levels are used). |

`EffectLabels` |
a character vector with the labels of the effects (default = NULL, which implies that the corresponding labels of the model coefficient are used). |

`EffectsMatrix` |
matrix defining contrasts to be compared (bypasses the EffectIndices, default is NULL, meaning that standard inference is performed). |

`ParBootstrap` |
logic flag indicating whether the confidence intervals should be calculated with parametric bootstrap (default is false, i.e. the Wald confidence interval is used). Not implemented for objects of class lme. |

`Nboots` |
number of bootstrap samples used for the confidence interval. (default = 999). |

`SignificanceLevel` |
the significance level of the pairwise comparisons (default = 0.05). |

`UpperCase` |
should upper case letters be used for labelling the groups (default is FALSE). |

`RankLabels` |
should the labels of the grouping be sorted according to the value of the response (default=TRUE) |

`WaldApproximation` |
logic flag indicating whether a Wald approximated test should be used (defaut = FALSE). |

`CalcClusters` |
should the clusters be calculated and displayed instead of grouping (Default is FALSE) |

`QUIET` |
flag indicating whter the (large) output of the multcomp library should be temporarily re-directed (default = TRUE). |

`PlotAdj` |
should the associated graph be printed(default = FALSE). |

`digits` |
number of digits in the output (default = 4) |

`padjust` |
method for correcting the p-values (before the calculations are performed) as in the function p.adjust (Default is NULL, indicating that no multiple testing corrections are used) |

`Scale` |
a scaling factor multiplying the output table (default = 1, i.e., no scaling is used). |

`Location` |
a location term added to the output table (default = 0, i.e., no location shift is performed). |

`isBinomialModel` |
a logical flag indicating whther the model is a binomial model different than the Bernoulli (default = FALSE, i.e. not a binomial model). |

`BackTransform` |
should the parameters and CIs be back transformed by applying the inverse link function (default = TRUE) |

The function contructs, using the supplied matrix of p-values for all pairwise comparisosns, an undirected graph with vertices representing the levels of the effects, using the convention that two vertices are connected by an edge iff the p-value for testing equality the two vertices is larger than the prefixed significance level. The maximal cliques of this graph form the grouping of the levels of the effects.

Perform post hoc analyses via pairwise comparisons of all the effect levels, or of a supplied subset of effects (using the parameter "EffectIndices") or even linear combinations of effects (using the parameter "EffectsMatrix")

an object of (S3) class "PostHoc" with methods for print, summary, plot, barplot and lines defined. An object of class "PostHoc" contails the effects, grouping, the matrix of p-values of all pairwise comparisons, the graph (Gr) of adjacency, the confidence intervals of the effects, the significance levels, the number of digits to be used for printing, the list of maximal cliques of the graph Gr, the clusters (if calculated).

Rodrigo Labouriau

1 2 3 | ```
MM <- glm(Y ~ Treatment+0, data=DeIdentifiedExample)
GG <- posthoc(MM)
print(GG)
``` |

```
Loading required package: igraph
Attaching package: ‘igraph’
The following objects are masked from ‘package:stats’:
decompose, spectrum
The following object is masked from ‘package:base’:
union
Loading required package: multcomp
Loading required package: mvtnorm
Loading required package: survival
Loading required package: TH.data
Loading required package: MASS
Attaching package: ‘TH.data’
The following object is masked from ‘package:MASS’:
geyser
Levels ParameterCI
1 TreatmentA 10.1546(8.903-11.4063)a
2 TreatmentB 16.2905(15.0389-17.5422)d
3 TreatmentC 13.5463(12.2946-14.7979)bc
4 TreatmentD 14.5171(13.2655-15.7688)bcd
5 TreatmentE 16.1834(14.9318-17.4351)cd
6 TreatmentF 8.6771(7.4255-9.9288)a
7 TreatmentG 13.5065(12.2549-14.7582)b
```

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